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Communications of the ACM
Scopus
ISSN 0001-0782 · Association for Computing Machinery · 12 artikel di indeks
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Artikel Jurnal Teks lengkap
Talking about Large Language Models
Interacting with a contemporary LLM-based conversational agent can create an illusion of being in the presence of a thinking creature. Yet, in their very nature, such systems are fundamentally not like us.
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Computing Education in the Era of Generative AI
Challenges and opportunities faced by computing educators and students adapting to LLMs capable of generating accurate source code from natural-language problem descriptions.
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WinoGrande
Commonsense reasoning remains a major challenge in AI, and yet, recent progresses on benchmarks may seem to suggest otherwise. In particular, the recent neural language models have reported above 90% accuracy on the Winograd Schema Challenge (WSC), a commonsense benchmark originally designed to be…
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Understanding deep learning (still) requires rethinking generalization
Despite their massive size, successful deep artificial neural networks can exhibit a remarkably small gap between training and test performance. Conventional wisdom attributes small generalization error either to properties of the model family or to the regularization techniques used during…
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Datasheets for datasets
Documentation to facilitate communication between dataset creators and consumers.
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Deep learning for AI
How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding language?
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NeRF
We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene using a fully connected (nonconvolutional) deep network…
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Some simple economics of the blockchain
Blockchain technology can shape innovation and competition in digital platforms, but under what conditions?
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A decade of social bot detection
Bots increasingly tamper with political elections and economic discussions. Tracing trends in detection strategies and key suggestions on how to win the fight.
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Green AI
Creating efficiency in AI research will decrease its carbon footprint and increase its inclusivity as deep learning study should not require the deepest pockets.
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A domain-specific supercomputer for training deep neural networks
Google's TPU supercomputers train deep neural networks 50x faster than general-purpose supercomputers running a high-performance computing benchmark.
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Domain-specific hardware accelerators
DSAs gain efficiency from specialization and performance from parallelism.